SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 31–40 of 2226 papers

TitleStatusHype
Triple equivalence for the emergence of biological intelligenceCode1
Divide-and-Conquer Predictive Coding: a structured Bayesian inference algorithmCode1
Persistent Sampling: Enhancing the Efficiency of Sequential Monte CarloCode1
Torchtree: flexible phylogenetic model development and inference using PyTorchCode1
Poisson Variational AutoencoderCode1
Gaussian Stochastic Weight Averaging for Bayesian Low-Rank Adaptation of Large Language ModelsCode1
PICLe: Eliciting Diverse Behaviors from Large Language Models with Persona In-Context LearningCode1
CoS: Enhancing Personalization and Mitigating Bias with Context SteeringCode1
Unifying Bayesian Flow Networks and Diffusion Models through Stochastic Differential EquationsCode1
Bayesian Diffusion Models for 3D Shape ReconstructionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified